Over the past 50 years engineers, scientists, and physicians working in biology, medicine, and physiology have constructed an entire, self-consistent intellectual framework using monolayer monocultures on plastic. Currently there are only a limited number of techniques for growth and maintenance of cell cultures. As shown in FIG. 1, these include a Petri dish 100 that enables the culture of cells 103 in cell-culture media 102; a culture flask 110 with removable cap 111; a well plate 120 with wells 121; and a well-plate 120 that supports a Transwell device 130 that has as its bottom a porous filter 132 that supports cells 103 and enables communication through the cell layer of culture media 102 on the outside of the wall of the insert 131 with culture media on the inside. Cells are grown to high density in a perfused hollow fiber bioreactor 140 that has cells 103 growing on either the inside, outside, or both sides of hollow fibers 146. The end caps 142 and 143 couple the inlet and outlet flows 148 of culture media 102. Additional ports, not shown, can provide access to the fluid and cells outside of the fibers. Adherent or suspended cells can be grown in high volume in a rotating bioreactor 150, in which the bottle 151 with cap 111 is supported on rollers 153 that are rotated by a mechanism 155 to ensure continuous mixing of the solution inside the bottle, thereby nourishing the cells that are either adherent to the inner surfaces of the bottle or are suspended in the media 102. Cells can be grown at high density in a suspended bead bioreactor 160 that utilizes a magnetic stirrer 161 and magnet 168 or a direct mechanical connection 162 attached to the top 165 to rotate a paddle 167. As a result of the rotation of the paddle, cells 103 attached to neutral-buoyancy beads 169 are kept in close contact with the volume of media 102. These examples are representative of the many types of systems that have been devised to culture cells in vitro. The ultimate accomplishment of this fifty-year effort has been the introduction of the multi-well, micro-titer plate that can allow individual experiments to be conducted in as many as 1536 wells, each of which contains about 8 μL of cell culture media, serviced by an automated robot (FIG. 2) that moves well plates between different preparation and measurement stations and incubators.
There are a number of major limitations of existing cell culture technology. The small-volume wells with a supposedly homogeneous cellular phenotype do not recapitulate the heterogeneous tissue microenvironment. Nutrient and metabolite transport is limited by diffusion. The local microenvironment, and hence the cellular phenotype and dynamic response, may differ between the corners and the center of each well. It is hard to create controlled concentration gradients. It is difficult to reverse the course of an experiment—it is easier to inject a drug, nutrient, or toxin than to wash it out. The plastic of Petri dishes, flasks, and well plates for growing adherent cells is quite foreign to a realistic biological environment: the Young's modulus for cell culture plastic is 10,000 to 100,000 times higher than that of living tissue. Only bone has a stiffness that approaches that of cell culture plastic. It is difficult to provide the shear forces that are required to maintain endothelial and epithelial polarization in Petri dishes or well plates. It is also difficult to provide appropriate mechanical forces to cells such as is experienced in the heart, skeletal and smooth muscle, lungs, and skin. The centralized robotic fluid handler and the isolated plate reader are not well suited for fast, real-time, closed-loop control of dynamic cellular processes. It is difficult to invoke complex exposure protocols or to create well-to-well connections that simulate organ-organ interactions. The most important convention in cell culture is the desire to change culture media only once every day or two. This infrequent media change results in the volume of culture media being approximately 1000 times that of the cells themselves. Hence paracrine and autocrine factors and metabolites secreted by cells are diluted a thousand-fold by the infrequent changing of the media above the cells.
FIG. 2 shows a robot well-plate handling system 200 including, for example, a robot well-plate manipulation system 201 with a rotating base 202 and an articulated arm 203 that has been optimized to allow a gripper jaw 204 to perform automated transfers of well plates 120 between various fixed stations, which include, but are not limited to, incubators 210, fluid handlers 220 with internal X-Y position control of pipettes 221 and 222, plate readers 230, bar-code readers 235, lid hotels 240, plate sealers 250, plate stackers 205, and other plate-oriented instruments 270 and 260, as shown in FIG. 2B. The entire system, if desired, can be enclosed in a sterile environment supported by windows 280 and HEPA filters 290, as shown in FIG. 2A. While it might be possible to create a jaw system 204 that can handle a pair of interconnected plates, as the number of interconnected plates grows it obviously becomes impractical to use this topology to manipulate the plates. Point-to-point transfer is not suitable for the manipulation of a plurality of interconnected modules.
Three commercial well-plate fluid-handling systems as indicated by 220 in FIG. 2 are in widespread use and are worthy of examining: the Agilent Bravo™ Liquid Handling System; the Agilent Encore Multispan™ Liquid Handling System, and the Hamilton MICROLAB® STAR Liquid Handling Workstation. The Bravo has a single 96-pipette movable head that can X-Y address (221, 222) a 3×3 array of well plates. It has an on-board gripper that can be used to move a well plate from one location to another. It provides no means for interconnecting multiple well plates or moving more than one well plate at a time. The newer Agilent Encore Multispan has an articulated robot arm and eight variable-span pipetters that provide independent X and Y axis motion. It can pipette to and from up to 24 well plates, and its gripper can reach up to 32 well plates stored on a common deck. It provides no means for interconnecting multiple well plates or moving more than one well plate at a time. The Hamilton MICROLAB® STAR system has both a 96 or 384 pipetting head and 8 or 16 multi-span individual pipettes and other features. It has both a plate gripper and a separate articulated arm gripper. In the context of this invention, it provides a variety of Eppendorf and well-plate carriers that can be manually delivered to an automatic feed system that uses a rack and pinion system to slide these carriers into predefined locations, with the gear-teeth of the rack being formed into the bottom of one side of the carrier. The system has 30 parallel tracks that can support tube or well-plate carriers. The carriers can be equipped with a variety of functions, including thermal regulation or onboard, addressable single-well imaging. Most important, the system does not provide the capability of the autonomous relocation of carriers from one predefined location to another, nor is there a provision to move these carriers from this instrument to an incubator or other instrument spatially separated from the fluid-handling unit. Both of these operations must be performed manually. These systems are viewed as exemplary of an entire class of fluid-handling robots utilized for high-throughput well-plate screening. None of these support fluidic communication between different well plates.
The recognition of the limitations of conventional cell culture techniques is leading to an increased interest in the creation of heterogeneous cell cultures growing in three-dimensional (3D) extracellular matrices with organotypic perfusion and stiffness in addition to proper mechanical, chemical, and electrical cues. Furthermore, the advance of biology, medicine, and physiology will be facilitated by the introduction of tools and techniques that enable closed-loop control of biology, including the dynamic control of extracellular matrix chemistry and mechanical properties. The challenges of closed-loop control of biological systems are summarized in the review article: P. R. LeDuc, W. C. Messner, and J. P. Wikswo, “How do control-based approaches enter into biology?” Annu. Rev. Biomed. Engr. 13:369-396, 2011. Tools and techniques enabling closed-loop control of biology would also support automated design of experiments, wherein cell type, matrix chemistry and architecture, and the addition or subtraction of metabolic and signaling molecules and other cues are adjusted automatically by machine learning algorithms that are attempting to identify and test hypotheses related to biological function. As an example, there is a need to refine the selection and timing of the application of cytokines and other signaling molecules whose sequence and concentration are optimized to cause an induced pluripotent stem cell (iPSC) to differentiate into a desired, specific cell type. FIG. 3 shows several well-plate topologies in common use, such as a single well plate 120 (FIG. 3A), a row of well plates 120 (FIG. 3B), a rectangular array of well plates 120 (FIG. 3C), or a stack of well plates 120 (FIG. 3D). None of these are interconnected, and in none of these devices or topologies do different, distinct populations of cells communicate with other distinct cell populations. Combinatorics alone will not be sufficient for identifying the complex chemical control trajectories required to obtain a particular cell phenotype. Furthermore, 3D bioreactors benefit from quantitative, real-time measurements of a breadth of analytes that span different molecular classes, such as proteins, oligonucleotides, lipids, carbohydrates, peptides and other small molecules. The difficulty is that most existing bioanalytical techniques are slow and require substantial sample volumes—both of which compromise the ability to control in real time a small 3D tissue bioreactor, and are often applied in a targeted manner that detects only preselected molecules of interest. Rapid, low-volume, untargeted assays are needed to track the complex biosignatures of cellular differentiation, development, and the response to growth factors, nutrients, toxins and other chemical, electrical, and mechanical stimuli.
Organs-on-chips (OoCs) and 3D tissue engineering present promising new technologies in the fields of automated biology, physiology, and the discovery, development, and toxicity/safety screening of new pharmaceuticals. OoCs are unique in the sense that an OoC can provide significant data on drug/organ interactions and multi-organ physiology without the use of animal studies. To date, there has been little research into integrating these organ systems with intra-device fluid handling. Two recent journal articles provide a critical review of coupled OoCs: “Engineering Challenges for Instrumenting and Controlling Integrated Organ-on-Chip Systems,” Wikswo et al., IEEE Trans. Biomed. Eng., 60:682-690 (2013), and “Scaling and Systems Biology for Integrating Multiple Organs-on-a-Chip,” Wikswo et al., Lab Chip, 13:3496-3511 (2013), which together provide one of the most thorough overviews of the major technical and biological challenges that need to be addressed in the development of coupled microphysiological systems. The challenges facing OoC design, development, and use are paralleled by comparable challenges in the engineering of tissue, for example tissue-engineered cardiac valves, blood vessels, peripheral nerve, or skin grown from the iPSCs of a patient whose tissues are in need of repair or grafting due to illness or injury. A multi-disciplinary approach is required to integrate these “organs” with the required maintenance devices for their growth and support, and ultimately may enable use of machine learning algorithms driving automated robotic scientists that can perform biological experiments without user intervention.
Therefore, a heretofore unaddressed need exists in the art to address the aforementioned deficiencies and inadequacies.